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arXiv · 1308.1126

Image interpolation using Shearlet based iterative refinement

H. Lakshman·W. -Q Lim·H. Schwarz·D. Marpe·G. Kutyniok·T. Wiegand
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Abstract

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering, (b) promoting sparsity in a selected dictionary through iterative thresholding, and (c) extracting high frequency information from the approximation to refine the initial estimate. For the sparse modeling, a shearlet dictionary is chosen to yield a multiscale directional representation. The proposed algorithm is compared to several state-of-the-art methods to assess its objective as well as subjective performance. Compared to the cubic spline interpolation method, an average PSNR gain of around 0.8 dB is observed over a dataset of 200 images.

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H. Lakshman, W. -Q Lim, H. Schwarz, D. Marpe, G. Kutyniok, T. Wiegand. 2013-08-05. Image interpolation using Shearlet based iterative refinement. https://arxiv.org/abs/1308.1126

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